In the context of multi-view camera array images (e.g., images from two or more views of a scene), creating a sense of depth and perception in a two-dimensional static image presented to a viewer makes the image more appealing. For example, the motion parallax effect may be used to present more appealing images to a user such that a scene is captured from different viewpoints using a multi-camera array system and the intermediate views are synthesized, so that the viewer can perceive the depth information in the scene when the image is viewed from different angles.
Current techniques for synthesizing intermediate views include estimating an optical flow between image pairs and using the estimated flow to predict the intermediate image. Some optical flow techniques use naïve mathematical approaches, which provided limited accuracy, while others use patch-based approaches to predict the intermediate image, which provide good accuracy in a limited set of scenarios but are limited in the disparities they can handle and are computationally very intensive.
It may be advantageous to improve intermediate view synthesis in multi-view camera array or other multi-view contexts both in terms of accuracy and computation efficiency. It is with respect to these and other considerations that the present improvements have been needed. Such improvements may become critical as the desire to display multi-view images and intermediate synthesized images in a variety of contexts becomes more widespread.